Role of Transient Elastography (Fibroscan) in Early prediction of Hepatitis C Virus Related Hepatocellular Carcinoma

Document Type : Original Article

Authors

1 Hepatogastroenterology and infectious diseases, faculty of medicine, Al-Azhar University, Egypt

2 Hepatogastroenterology and infectious diseases, faculty of medicine, Al-Azhar University, Egypt.

3 hepatology,gastroentroogy and infectious diseases, al azhar university , cairo ,egypt

4 Hepatogastroenterology and Infectious diseases department, Faculty of Medicine- Cairo University, Egypt.

5 Diagnostic radiology department, Faculty of Medicine- Cairo University, Egypt.

Abstract

Background: Hepatocellular carcinoma (HCC) is the fifth-leading cause of cancer-related deaths globally. Liver biopsy is the gold standard for diagnosing liver fibrosis and cirrhosis. Instead of a liver biopsy, a number of noninvasive diagnostic tools for assessing hepatic fibrosis as a risk factor for HCC, such as fibroscan.
Aim of work: Assess the role of Transient Elastography (Fibroscan) in prediction of (HCC) in chronic hepatitis C virus patients.
Subjects and methods: A case-control study included 133 patients with cirrhosis and HCC and 133 patients with HCV-Liver cirrhosis without HCC was carried out. Each patient had their medical history taken, and thorough clinical examination, they were assessed for liver stiffness using fibroscan, all patients underwent Triphasic CT scan, routine laboratory investigations were taken from each patient as liver function test, CBC and tumor markers.
Results: Males resembled the majority and patients with HCC were significantly older than those without HCC (p-value < 0.001). Our data showed that sensitivity analysis of liver stiffness measured by transient elastography (FibroScan) can be used to discriminate between cirrhotic group without HCC and HCC group at a cutoff level of > 24.3, with 90.5% sensitivity, 85.7% specificity, 86.4% PPV and 90% NPV (AUC = 0.941 & p-value less than 0.001).
Conclusion: Fibroscan can significantly predict HCC among patients post-HCV treatment using cutoff point of liver stiffness > 24.3 kPa.

Keywords


INTRODUCTION

Liver cell carcinoma (HCC) is the fifth commonly diagnosed malignancy globally and the third main factor for cancer related mortality.1-2 Because of the prominent incidence of hepatitis C virus and enhanced survival for cirrhotic patients, the prevalence of hepatocellular carcinoma in Egypt has grown significantly throughout the previous decade 3-5.

Improved liver cancer prognosis requires early detection and effective therapy. To that purpose, it is essential to define the high-risk populations for liver cancer and implement adequate screening and early detection programs for patients diagnosed with chronic liver disease6-7.

It has been proposed that hepatitis virus infection is the primary cause for HCC and correlated to poor

 

prognosis due to poor liver function of the underlying cirrhotic liver 8; nevertheless, hepatic cirrhosis is the significant risk factor irrespective of its origin 9.

Obtaining a histopathological diagnosis is the standard of care for quantitative evaluation of liver fibrosis, unfortunately, liver biopsy is expressing many drawbacks as invasiveness, sampling errors, and interobserver variability, because of these features liver biopsy is unfeasible for serial examinations of chronic liver disease patients and follow up 10.

Recently many noninvasive diagnostic tools has been proposed for early diagnosis of primary liver tumors and follow-up of cirrhotic patients, Fibroscan became feasible to assess the elasticity of the liver by employing transient elastography 11. The severity of liver fibrosis must be accurately determined for patient prognosis and monitoring 12.

Recently, a study has correlated that liver stiffness measured by Fibroscan with risk for development of HCC in the European population 13; however, the risk of HCC was extrapolated form the degree of cirrhosis measured by Fibroscan indicating that HCC-related liver stiffness couldn’t be precisely evaluated 14.

Thus, our goal was to assess the role of Transient Elastography (Fibroscan) in prediction of (HCC) in chronic hepatitis C virus patients

PATIENTS AND METHODS

We conducted a case control study including 133 HCC patients, They were recruited from the multidisciplinary HCC clinic at Kasr-Alainy Hospital, Cairo University, Egypt and Cairo University's endemic medicine department, we recruited 133 patients with liver cirrhosis without HCC to serve as a control group. Before enrollment in the study, all participants gave their informed consent in the period from February 2022 to August 2022. All patients with Chronic HCV infection or hepatitis C related HCC who did not receive any previous treatment for HCC were eligible for inclusion in the current study.

HCC was diagnosed based on the standards in the American Association's guidelines for the study of Liver Diseases (AASLD), using computerized tomography (CT) or magnetic resonance imaging (MRI) techniques and alpha-fetoprotein (AFP) 15. Patients with other chronic liver diseases than HCV e.g., HBV, alcohol related, autoimmune liver disease and patients co-infected with HIV and HCC patients who receive any previous treatment to HCC were excluded form final analysis.

All studied patients were subjected to the following: Taking their history including Personal history such as (name, age, gender, occupation, residence and special habit of medical importance), past medical history (DM, HCV, HBV infection, HCC, and blood transfusion). Clinical assessment which includes General examination:For evidence of stigmata of chronic liver disease (Jaundice, foetor hepaticus, impaired consciousness, palmer erythema, spider naevi, finger clubbing, jaundice, gynecomastia, feminine distribution of pubic hair, testicular atrophy, cachexia and peripheral edema). Abdominal examination: with special emphasis on (Liver: size, border, surface, consistency, tenderness, pulsation, Spleen: size, notch and ascites) and dilated veins.

Baseline laboratory tests including complete blood count (CBC), liver function tests, ALT and AST, Albumin, INR and total/direct bilirubin, Renal functions (Urea, Creatinine), Alpha-fetoprotein (AFP) was assessed using Latex Immunoturbidimetric Method, and Viral hepatitis markers including (HCV Ab, HBVs Ag) using ELISA technique.

Pelviabdominal Ultrasound was done by the same operator for all patients for examination of liver echotexture & size, size of spleen, presence or absence of ascites, tumor characteristics (focal lesion site, size and number, portal vein and abdominal lymph node assessment). Triphasic CT of abdomen and pelviswas done to diagnose and staging of HCC.

Transient Elastography (Fibroscan), Patients were placed in the dorsal decubitus posture with the right arm at the maximum abduction, and the probe was applied on the right hepatic lobe through intercostal spaces. The probe's transducer tip was placed between the ribs and coated with coupling gel. The operator detected a portion of the liver free of large vascular structures and distant from HCC with the help of an ultrasonic time-motion imaging. Each subject underwent up to 10 successful measurements. The success rate of at least 60% was reliable. If the interquartile range (IQR) to median value ratio was less than 0.30, only then is the median value of successful measurements chosen as representative of the LSM value in a given patient16. The following criteria were used to  diagnose cirrhosis: transient elastography greater than 14 kPa, histology, and radiographic or endoscopic indications of portal hypertension 17.

Sample size: we used a convenient period sampling, it included all eligible patients who were assessed in the multidisciplinary HCC clinic at Kasr-Alainy Hospital during the period from Feb 2022, till Aug 2022.

Ethical considerations: study protocol was reviewd and approved by the ethical committee of AlAzhar university (Ethical approval number, 000089).

Statistical analysis: The statistical package for the social sciences (SPSS) version 28 was used to code and enter the data (IBM Corp., Armonk, NY, USA).  Quantitative data were summarized using the mean, standard deviation, median, minimum, and maximum; categorical data were described using frequency (count) and relative frequency (%). The non-parametric Kruskal-Wallis and Mann-Whitney tests were used to compare quantitative variables. In order to compare categorical data, the Chi square (2) test was used. When the anticipated frequency is < 5, the exact test was used in its place. The Spearman correlation coefficient was used to determine correlations between quantitative variables. P-values greater than 0.05 were regarded statistically significant.  


RESULTS

A case control study included 133 patients with liver cirrhosis and 133 patients with HCC was conducted.

 

Liver cirrhosis group

(n = 133)

HCC group

(n = 133)

P-value

Sex

Male

49

36.8%

105

78.9%

< 0.001

Female

84

63.2%

28

21.1%

Age (years)

Median (IQR)

54.0 (37.0- 57.0)

63.0 (56.0- 68.0)

< 0.001

Range

19.0 – 73.0

34.0 – 75.0

BMI (Kg/m2)

Median (IQR)

23.80 (21.74- 28.70)

24.40 (22.10- 28.30)

0.329

Range

19.50 – 34.0

19.5 – 30.10

Table 1: Basic characteristics of the studied groups Patients with HCC were significantly older in age and the majority of them were males (p-value < 0.001). The studied groups did not differ with regard to their weight, height or BMI.

 

 

 

Groups

P-value

Liver cirrhosis group

HCC group

Diabetes mellitus

3

2.3%

5

3.8%

0.473

Cigarette Smoking

Non-smoker

109

82.0%

88

66.2%

0.003

X- smoker

0

0.0%

6

4.5%

Smoker

24

18.0%

39

29.3%

Smoking duration (years)

Median (IQR)

21.50

(18.5- 30.0)

22.0

(20.0- 40.0)

0.257

Range

3.0 – 40.0

5.0 – 50.0

Blood transfusion

6

4.5%

14

10.5%

0.063

History of hematemesis and Melena

21  

18.75%

32

24.06%

0.091

History of hepatic encephalopathy

17

12.78%

29

21.80%

0.052

Treated with Sof/Dacla 12 wk

88

66.17%

73

54.89%

 

Treated with Sof/Dacla  24 wk

5

3.76%

7

5.26%

 

Treated with Sof/Dacla/Riba 12 wk

38

28.57%

46

34.59%

 

Treated with Sof/Dacla/Riba 24 wk

0

0.00%

1

0.75%

 

Treated with Sof/Led 12 wk

1

0.75%

0

0.00%

 

Treated with Sof/Led/Riba 12 wk

0

0.00%

3

2.26%

 

Treated with Sof/Led/Riba 24 wk

0

0.00%

1

0.75%

 

Treated with INF/Sof/Riba 12 wk

1

0.75%

2

1.50%

 

                       

Table 2: Comparisons between studied groups as regard medical history Patients with HCC were far more likely to smoke cigarettes (p-value 0.003). In addition, we found no significant difference among the studied groups regarding diabetes mellitus or previous blood transfusion, history of hematemesis and melena, as well as, history of hepatic encephalopathy (p-value > 0.05).

 

 

 

Groups

P-value

Liver cirrhosis group

(n = 133)

HCC group

(n = 133)

Liver size

Average

127

95.5%

96

72.2%

<0.001

 

Enlarged

6

4.5%

16

12.1%

 

Shrunken

0

0.0%

21

15.8%

 

Spleen

Average

125

94.0%

58

43.6%

<0.001

 

Enlarged

7

5.3%

74

55.6%

 

Surgically removed

1

0.8%

1

0.8%

 

Ascites

0

0.0%

4

3.0%

0.122

 

                 

Table 3: Comparisons between studied groups as regard abdominal examination There were highly statistically significant difference between studied groups as regard liver and spleen size (p-value < 0.001) the groups did not differ regarding the presence of ascites (p-value > 0.05).

Triphasic CT results

Number

Percent

Number of lesions

1 lesion

74

55.6%

2 lesions

21

15.8%

3 lesions

5

3.8%

>3 lesions

33

24.8%

Size of lesions in cm

Mean ±SD

4.25 ± 2.45

Table 4: radiological characteristics of hepatic lesions among the HCC group.

In the current study, most of HCC lesions were solitary accounting for 55.6%, followed by >3 lesions in 24.8%, then 2 lesions in 15.8% and 3 lesions in 3.8%, with mean size of all lesions 4.25 ± 2.45 cm.

 

Liver cirrhosis group

HCC group

Mann-Whitney U test

Median

Min.

Max.

Median

Min.

Max.

Test value

P-value

Hemoglobin

13.0

8.5

17.7

11.9

1.0

18.4

2.320

0.02

 

WBC

5.6

2.3

12.7

5.9

2.2

57.0

0.678

0.498

Platelets

224.0

40.0

440.0

129.50

36.0

336.0

8.348

<0.001

Total Bilirubin (mg/dl)

.69

.10

7.00

1.20

.10

7.00

-8.152

<0.001

AST (U/L)

47.00

7.00

565.00

73.00

7.00

565.00

-6.936

<0.001

ALT (U/L)

47.00

4.30

551.00

66.00

4.30

551.0

-3.737

<0.001

Albumin (g/dl)

4.1

2.00

4.60

3.73

2.00

4.60

-9.840

<0.001

INR

1.00

.90

1.67

1.3

1.00

2.11

-8.730

<0.001

AFP (ng/ml)

3.5

.50

77.28

62.5

2.3

61344.0

-10.96

<0.001

Table 5: Laboratory characteristics of the studied groups. Patients with HCC had significantly lower hemoglobin level and platelet count and higher white blood cells count as compared to patients with liver cirrhosis without HCC. In addition, patients with HCC showed significantly more deteriorated synthetic liver functions (higher bilirubin and lower serum albumin and INR), they also had higher liver enzymes and serum AFP (p value <0.001).

 

 

 

Groups

P-value

Liver cirrhosis group

(n = 133)

HCC group

(n = 133)

Steatosis grade

S0

69

51.9%

92

69.2%

0.001

S1

19

14.3%

22

16.5%

S2

27

20.3%

8

6.0%

S3

18

13.5%

11

8.3%

CAP

Median (IQR)

224.0

(201.0- 267.0)

201.0

(176.0- 243.0)

<0.001

Range

100.0 – 400.0

100.0 – 346.0

Liver stiffness

Median (IQR)

23.50 (18.5- 30.0)

26.0 (20.0- 40.0)

<0.001

Range

3.0 – 40.0

5.0 – 50.0

Table 5: Comparisons between studied groups as regard steatosis grade, CAP and liver stiffness measurements. Our study showed that patients with HCC had significantly lower steatosis as measured by CAP using transient elastography (p-value < 0.001). Regarding steatosis score; 85.7% of patients with HCC had no or mild steatosis (S0 and S1) as compared to 66.2% of patients without HCC. On the opposite side, patients with HCC had significantly higher liver stiffness as compared to patients without HCC (p-value < 0.001).

 

Cut off

AUC

Sensitivity

Specificity

PPV

NPV

p-value

FibroScan

> 24.3

0.941

90.5%

85.7%

86.4%

90%

< 0.001

Table 6: Diagnostic performance of FibroScan in discrimination of liver cirrhosis and HCC in chronic HCV patients.

Using ROC curve, it was shown that FibroScan can be used to predict HCC using cutoff level of > 24.3, with 90.5% sensitivity, 85.7% specificity, 86.4% PPV and 90% NPV (AUC = 0.941 & p-value < 0.001) (table 6, figure 1).

 

Fig. 1: ROC curve of FibroScan in discrimination of liver cirrhosis cirrhotic group and HCC group


DISCUSSION

Hepatocellular carcinoma (HCC) is the fifth most cause of cancer-related death worldwide 18. Although there has been substantial progress in attaining a high sustained virological response (SVR) in individuals with liver cirrhosis, the risk of developing HCC remains roughly 1% per year after reaching SVR 19.

Liver biopsy is the gold standard that can be used to diagnose liver fibrosis and cirrhosis, although it is an invasive technique with rare but potential consequences. Instead of a liver biopsy, a number of noninvasive indicators for assessing hepatic fibrosis as a risk factor for HCC have been proposed 20-21.

Except for hepatic congestion, severe hepatic infections, or cholestasis, which may overestimate cirrhosis with Fibroscan, the accuracy of Fibroscan diagnosis of hepatic cirrhosis has been largely proven in many chronic liver diseases 22.

Recently, liver cancer risk in the European population was examined using Fibroscan measurements of liver stiffness 13. Furthermore, the efficiency of Fibroscan  in determining the probability of HCC has not been fully investigated 10.

Thus, we carried out case-control research to assess the role of Transient Elastography (Fibroscan) in early detection of HCC in chronic hepatitis C virus patients. The study was conducted on 133 patients with liver cirrhosis but no HCC and 133 patients with cirrhosis and HCC.

Our results showed that HCC group was significantly older in age and with male predominance (p-value < 0.001). Cigarette smoking was significantly more common in patients with HCC (p-value 0.003).

These results were in accordance with many reported in literature that revealed old age, male gender, and cigarette smoking were correlated with a higher risk for development of HCC. HCC incidence peaks at the age of seventy, while cases before the age of forty are extremely rare 23. As well, between 250,000 and 1,000,000 new cases are reported globally each year with a male predominance and male to female ratio 2:1 and in some countries 4:1 24, some reports showed that males not only having higher incidence but also higher relapse rate 25.

However, findings in our were inconsistent with the study was done by Ebrahim et al.,10 who conducted a case control study including 25 cirrhotic patients and 25 HCC patients and results showed that HCC group had significantly higher BMI while age and gender was not significantly different. Reasons for this include the small sample size of the later research compared to the current one.

 Regarding liver and spleen size, there was a remarkable statistical significance difference between the analyzed groups in the current study (p-value < 0.001). our results are consistent with large cohort study that stated having a larger spleen capacity is a major predictor of developing HCC (HR = 2.13, p = 0.009) 26.

Shrunken liver is a common finding in late stages of liver cirrhosis, which is well known as the most prevalent underlying etiology of HCC development on top of cirrhosis as HBV and HCV induced liver cirrhosis increase the risk of HCC up to 8.73‐fold, and 7.07‐fold respectively 27.

These findings disagree with the study conducted by Ebrahim et al.,10 who stated that prevalence of hepatomegaly and splenomegaly was similar between study groups with p values >0.05. Which can be explained by the limited sample in the later study.

Within this research, patients with HCC had significantly lower hemoglobin level and platelet count and higher white blood cells count as compared to patients with cirrhosis of the liver but no HCC. In addition, Patients with HCC demonstrated noticeably worsened synthetic liver functioning (higher bilirubin and lower serum albumin and INR), they also had higher liver enzymes and serum AFP (p value <0.001).

These findings are consistent with many reports in literature stating that erythropoietin and Thrombopoietin are produced by liver and kidneys, it stimulates the production and differentiation of megakaryocytes into mature platelets. During liver cirrhosis and advancing in HCC a marked decline of those factors has been reported leading to anemia and low platelet count 28-30.

Alpha Feto protein being a diagnostic test for HCC among cirrhotic patients with cutoff point 400–500 ng/ml is regarded as diagnostic for HCC reaching specificity of 100% 31, other studies reported lower cutoff points as 20 ng/ml as the cut-off point, the sensitivity rose to 78.9%, although the specificity declined to 78.1% 32.

In the present study, total bilirubin and INR are one of the components for classification of Child-Pugh classification and BCLC classification, elevated total bilirubin and/or bilirubin indicates advanced stages of HCC, this can explain the higher level of INR and low albumin 33-34.

Regarding steatosis, the current study showed that HCC patients had significantly lower steatosis as measured by CAP using transient elastography (p-value <0.001). Regarding steatosis score 87.7% of patients with HCC had no or mild steatosis (S0 and S1) as compared to 66.1% of patients without HCC. On the opposite side, patients who had HCC had also significantly higher liver stiffness in comparison to patients without HCC (p-value < 0.001).

 In patients with chronic HCV, hepatic steatosis has been associated to a greater risk of HCC, coupled with obesity and diabetes mellitus. With a prevalence ranging from 31% to 72%, hepatic steatosis is a well-established histopathologic characteristic of chronic HCV 35.

Ohata et al. 36 demonstrated that hepatic steatosis elevated the likelihood of developing HCC in patients with chronic HCV. When compared to those with no steatosis, those with steatosis had a 2.81-times higher likelihood of getting HCC.

Sedentary lifestyle and imbalanced dietary calories lay the foundation for nonalcoholic fatty liver (NAFL), which can evolve to nonalcoholic steatohepatitis borderline (NASH). NAFL with mild inflammation progresses to NASH, fibrosis, cirrhosis, and, consequently, hepatocellular cancer (HCC). In the context of therapeutic response or dietary modifications, steatosis and NASH seem to be quite dynamic and reversible. Whether liver cirrhosis and fibrosis are present or not, NASH and NAFL can led to liver cancer. In some cases, NASH can induce liver cancer by generating varied degrees of fibrosis (fibrosis stages F1-F3) and cirrhosis (F4). Fibrosis (F1-F3) development owing to NASH is more prevalent (34-42%) than fibrosis reversal (18-22%). Depending on the illness stage, the incidence of HCC might range from 2.4% to 12.8%. (with or without cirrhosis) 37.

Our data showed that sensitivity analysis of liver stiffness measured by transient elastography (FibroScan) can be used to discriminate between liver cirrhosis cirrhotic group and HCC group at a cutoff level of > 24.3, with 90.5% sensitivity, 85.7% specificity, 86.4% PPV and 90% NPV (AUC = 0.941 & p-value less than 0.001).

These findings were comparable to ones reported by Ebrahim et al.,10 who highlighted that Liver stiffness values >24 kPa in hepatitis C virus patients can significantly predict HCC presence with sensitivity 98.2%, specificity 83.8%, PPV 94.5%, NPV 77.3%, and overall diagnostic accuracy 89%.

Other study conducted by Tatsumi et al., 38 reported that liver stiffness exceeding 12 kPa was an independent risk factor for the incidence of HCC. Determining the optimal cutoff for HCC occurrence would be useful in evaluating HCC risks.

Rinaldi et al., 39conducted a cohort study and followed up 258 HCV positive patients till development of HCC, and conducted a sensitivity analysis, results showed that Fibroscan can significantly predict HCC among HCV positive patients using a cutoff value of liver stiffness measurement 27.8 kPa, showed 72% sensitivity and 65% specificity and AUC 69.1%, with p value 0.0001.

As well, Masuzaki et al., 13 demonstrated a 45.5 times elevated HCC risk in patients with Liver stiffness > 25 kPa in comparison to cases with TE < 10 kPa 40. Alder et al., revealed an elevated risk of HCC in cirrhotic patients with liver stiffness value > 30 kPa.

One strength point within this research is that it showed a large sample size of both cirrhotic and HCC patients. We faced few limitations of being single center study, and results can’t be generalized over the whole region, there is scarcity of evidence regarding the optimal cutoff point for liver stiffness to diagnose HCC.

CONCLUSION

Fibroscan can significantly predict HCC among patients post-HCV treatment using cutoff point of liver stiffness > 24.3 kPa.

REFERENCES
1.   McGlynn, K. A.; Petrick, J. L.; El-Serag, H. B., Epidemiology of Hepatocellular Carcinoma. Hepatology. 2021; 73 Suppl 1 (Suppl 1), 4-13.
2.   Tatsumi, A.; Maekawa, S.; Sato, M.; Komatsu, N.; Miura, M.; Amemiya, F.; Nakayama, Y.; Inoue, T.; Sakamoto, M.; Enomoto, N., Liver stiffness measurement for risk assessment of hepatocellular carcinoma. Hepatology research : the official journal of the Japan Society of Hepatology. 2015; 45 (5), 523-32.
3.   Abd-Elsalam, S.; Elwan, N.; Soliman, H.; Ziada, D.; Elkhalawany, W.; Salama, M.; Hawash, N.; Arafa, M.; Badawi, R.; Shehata, W. M.; Khalil, H. S.; Elmashad, N., Epidemiology of liver cancer in Nile delta over a decade: A single-center study. South Asian journal of cancer. 2018; 7 (1), 24-6.
4.   Negm, O.; Abou Saif, S.; El Gharib, M.; Yousef, M.; Abd-Elsalam, S., Role of low-molecular-weight heparins in prevention of thromboembolic complication after transarterial chemoembolization in hepatocellular carcinoma. European journal of gastroenterology & hepatology. 2017; 29 (3), 317-21.
5.   Elwan, N.; Salem, M. L.; Kobtan, A.; El-Kalla, F.; Mansour, L.; Yousef, M.; Al-Sabbagh, A.; Zidan, A. A.; Abd-Elsalam, S., High numbers of myeloid derived suppressor cells in peripheral blood and ascitic fluid of cirrhotic and HCC patients. Immunological investigations. 2018; 47 (2), 169-80.
6.   Zacharakis, G.; Aleid, A.; Aldossari, K. K., New and old biomarkers of hepatocellular carcinoma. Hepatoma Research. 2018; 4, 65.
7.   Chen, K.; Chang, P.-E.; Goh, G. B.-B.; Tan, C.-K., Surveillance for hepatocellular carcinoma - current status and advances. Hepatoma Research. 2018; 4, 72.
8.   Kanwal, F.; Khaderi, S.; Singal, A. G.; Marrero, J. A.; Loo, N.; Asrani, S. K.; Amos, C. I.; Thrift, A. P.; Gu, X.; Luster, M., Risk factors for HCC in contemporary cohorts of patients with cirrhosis. Hepatology. 2022; 7-18.
9.   Garrido, A.; Djouder, N., Cirrhosis: a questioned risk factor for hepatocellular carcinoma. Trends in Cancer. 2021; 7 (1), 29-36.
10. Ebrahim, A. E.; Shehata, M. A. H.; Abou-saif, S.; Hamisa, M. f.; Abd-Elsalam, S.; Yousef, M., Role of Fibroscan for early detection of hepatocellular carcinoma (HCC) in hepatitis C cirrhotic patients. Egyptian Journal of Radiology and Nuclear Medicine. 2020; 51 (1), 134.
11. Chin, J. L.; Pavlides, M.; Moolla, A.; Ryan, J. D., Non-invasive Markers of Liver Fibrosis: Adjuncts or Alternatives to Liver Biopsy? Frontiers in pharmacology. 2016; 7, 159.
12. Galle, P. R.; Forner, A.; Llovet, J. M.; Mazzaferro, V.; Piscaglia, F.; Raoul, J.-L.; Schirmacher, P.; Vilgrain, V., EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma. Journal of hepatology. 2018;69 (1), 182-236.
13. Adler, M.; Larocca, L.; Trovato, F. M.; Marcinkowski, H.; Pasha, Y.; Taylor-Robinson, S. D., Evaluating the risk of hepatocellular carcinoma in patients with prominently elevated liver stiffness measurements by FibroScan: a multicentre study. HPB. 2016; 18 (8), 678-83.
14. Pesce, A.; Scilletta, R.; Branca, A.; Nigro, L.; Montineri, A.; Larocca, L.; Fatuzzo, F.; Castaing, M.; Puleo, S., Does transient elastography (FibroScan®) have a role in decision making in hepatocellular carcinoma? HPB. 2012; 14 (6), 403-8.
15. Heimbach, J. K.; Kulik, L. M.; Finn, R. S.; Sirlin, C. B.; Abecassis, M. M.; Roberts, L. R.; Zhu, A. X.; Murad, M. H.; Marrero, J. A., AASLD guidelines for the treatment of hepatocellular carcinoma. Hepatology. 2018; 67 (1), 358-80.
16. Berger, M.; Matt, C.; Gönsch, J.; Hess, T., Is the Time Ripe? How the Value of Waiting and Incentives Affect Users’ Switching Behaviors for Smart Home Devices. Schmalenbach Business Review. 2019; 71 (1), 91-123.
17. Hegazy, O.; Allam, M.; Sabry, A.; Kohla, M. A. S.; Abogharbia, W.; Abogabal, A., Liver stiffness measurement by transient elastography can predict outcome after hepatic resection for hepatitis C virus-induced hepatocellular carcinoma. The Egyptian Journal of Surgery. 2019; 38 (2).
18. Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R. L.; Torre, L. A.; Jemal, A., Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians. 2018; 68 (6), 394-424.
19. Muzica, C. M.; Stanciu, C.; Huiban, L.; Singeap, A. M.; Sfarti, C.; Zenovia, S.; Cojocariu, C.; Trifan, A., Hepatocellular carcinoma after direct-acting antiviral hepatitis C virus therapy: A debate near the end. World journal of gastroenterology. 2020; 26 (43), 6770-81.
20. Soresi, M.; Giannitrapani, L.; Cervello, M.; Licata, A.; Montalto, G., Non invasive tools for the diagnosis of liver cirrhosis. World journal of gastroenterology. 2014; 20 (48), 18131-50.
21. Kang, J. S.; Lee, M. H., Noninvasive diagnostic and prognostic assessment tools for liver fibrosis and cirrhosis in patients with chronic liver disease. In Liver Cirrhosis-Update and Current Challenges. IntechOpen: 2017.
22. Kim, J. E.; Ryoo, B.-Y.; Ryu, M.-H.; Chang, H.-M.; Suh, D. J.; Lee, H. C.; Lim, Y.-S.; Kim, K. M.; Kang, Y.-K., Sorafenib for hepatocellular carcinoma according to Child-Pugh class of liver function. Cancer chemotherapy and pharmacology. 2011; 68 (5), 1285-90.
23. Janevska, D.; Chaloska-Ivanova, V.; Janevski, V., Hepatocellular Carcinoma: Risk Factors, Diagnosis and Treatment. Open access Macedonian journal of medical sciences. 2015; 3 (4), 732-6.
24. Liu, P.; Xie, S. H.; Hu, S.; Cheng, X.; Gao, T.; Zhang, C.; Song, Z., Age-specific sex difference in the incidence of hepatocellular carcinoma in the United States. Oncotarget. 2017; 8 (40), 68131-7.
25. Liang, T.; He, Y.; Mo, S.; Chen, Z.; Liao, X.; Zhou, X.; Yang, C.; Zhao, S.; Han, C.; Zhu, G.; Su, H.; Ye, X.; Peng, T., Gender disparity in hepatocellular carcinoma recurrence after curative hepatectomy. Annals of Hepatology. 2022; 27 (3), 100695.
26. Yoo, J.; Kim, S. W.; Lee, D. H.; Bae, J. S.; Cho, E. J., Prognostic role of spleen volume measurement using computed tomography in patients with compensated chronic liver disease from hepatitis B viral infection. European radiology. 2021; 31 (3), 1432-42.
27. Tarao, K.; Nozaki, A.; Ikeda, T.; Sato, A.; Komatsu, H.; Komatsu, T.; Taguri, M.; Tanaka, K., Real impact of liver cirrhosis on the development of hepatocellular carcinoma in various liver diseases-meta-analytic assessment. Cancer medicine. 2019; 8 (3), 1054-65.
28. Qamar, A. A.; Grace, N. D., Abnormal hematological indices in cirrhosis. Canadian journal of gastroenterology = Journal canadien de gastroenterologie. 2009; 23 (6), 441-5.
29. Chen, Y.-L.; Lin, H.-C.; Lin, K.-H.; Lin, L.-S.; Hsieh, C.-E.; Ko, C.-J.; Hung, Y.-J.; Lin, P.-Y., Low Hemoglobin Level Is Associated with the Development of Delirium after Hepatectomy for Hepatocellular Carcinoma Patients. PLOS ONE. 2015; 10 (3), e0119199.
30. Finkelmeier, F.; Bettinger, D.; Köberle, V.; Schultheiß, M.; Zeuzem, S.; Kronenberger, B.; Piiper, A.; Waidmann, O., Single measurement of hemoglobin predicts outcome of HCC patients. Medical oncology (Northwood, London, England). 2014; 31 (1), 806.
31. Gupta, S.; Bent, S.; Kohlwes, J., Test characteristics of alpha-fetoprotein for detecting hepatocellular carcinoma in patients with hepatitis C. A systematic review and critical analysis. Annals of internal medicine. 2003; 139 (1), 46-50.
32. Befeler, A. S.; Di Bisceglie, A. M., Hepatocellular carcinoma: diagnosis and treatment. Gastroenterology. 2002; 122 (6), 1609-19.
33. Reig, M.; Forner, A.; Rimola, J.; Ferrer-Fàbrega, J.; Burrel, M.; Garcia-Criado, Á.; Kelley, R. K.; Galle, P. R.; Mazzaferro, V.; Salem, R.; Sangro, B.; Singal, A. G.; Vogel, A.; Fuster, J.; Ayuso, C.; Bruix, J., BCLC strategy for prognosis prediction and treatment recommendation: The 2022 update. Journal of hepatology. 2022; 76 (3), 681-93.
34. Kok, B.; Abraldes, J. G., Child-Pugh Classification: Time to Abandon? Seminars in liver disease. 2019; 39 (1), 96-103.
35. Starley, B. Q.; Calcagno, C. J.; Harrison, S. A., Nonalcoholic fatty liver disease and hepatocellular carcinoma: a weighty connection. Hepatology. 2010; 51 (5), 1820-32.
36. Ohata, K.; Hamasaki, K.; Toriyama, K.; Matsumoto, K.; Saeki, A.; Yanagi, K.; Abiru, S.; Nakagawa, Y.; Shigeno, M.; Miyazoe, S., Hepatic steatosis is a risk factor for hepatocellular carcinoma in patients with chronic hepatitis C virus infection. Cancer. 2003; 97 (12), 3036-43.
37. Anstee, Q. M.; Reeves, H. L.; Kotsiliti, E.; Govaere, O.; Heikenwalder, M., From NASH to HCC: current concepts and future challenges. Nature Reviews Gastroenterology & Hepatology. 2019; 16 (7), 411-28.
38. Tatsumi, A.; Maekawa, S.; Sato, M.; Komatsu, N.; Miura, M.; Amemiya, F.; Nakayama, Y.; Inoue, T.; Sakamoto, M.; Enomoto, N., Liver stiffness measurement for risk assessment of hepatocellular carcinoma. Hepatology Research. 2015; 45 (5), 523-32.
39. Rinaldi, L.; Guarino, M.; Perrella, A.; Pafundi, P. C.; Valente, G.; Fontanella, L.; Nevola, R.; Guerrera, B.; Iuliano, N.; Imparato, M., Role of liver stiffness measurement in predicting HCC occurrence in direct-acting antivirals setting: a real-life experience. Digestive diseases and sciences. 2019; 64 (10), 3013-9.
40. Masuzaki, R.; Tateishi, R.; Yoshida, H.; Goto, E.; Sato, T.; Ohki, T.; Imamura, J.; Goto, T.; Kanai, F.; Kato, N., Prospective risk assessment for hepatocellular carcinoma development in patients with chronic hepatitis C by transient elastography. Hepatology. 2009; 49 (6), 1954-61.